Video‐based facial expression recognition by removing the style variations. Issue 7 (1st July 2015)

• Record Type: Journal Article
• Authors: Mohammadian, Amin; Aghaeinia, Hassan; Towhidkhah, Farzad
• Is Part Of: IET image processing. Volume 9:Issue 7(2015)
• Page Start: 596
• Page End: 603
• Publication Date: 2015-07-01
• Subjects: face recognition -- emotion recognition -- image classification -- image sequences -- support vector machines -- hidden Markov models -- video signal processing; hidden Markov models -- binary support vector machines -- image sequences -- image classification -- STM -- style transfer mapping -- person‐independent classifier -- semi‐style‐free space -- person‐independent facial expression recognition -- video‐based facial expression recognition; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2013.0697
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : This study examines the performance of person‐independent facial expression recognition improved by adapting the system to a given person. The proposed method transfers the style of particular subjects to the semi‐style‐free space. There is no need to change the person‐independent classifier in order to improve the performance. The style transfer mapping (STM) has been proposed in image‐based classification. The challenges of employing this technique in video‐based facial expression recognition are: estimating STM from image sequences of each subject (adaptation data) and projecting new sequential data of each subject in semi‐style‐free space. A mixture of 'binary support vector machines' and 'hidden Markov models' were employed to overcome these challenges. Moreover, virtual samples generated by using the person's neutral samples were used to estimate STM. Experimental results on the CK+ database confirm the efficiency of the proposed method in recognition rate improvement.